Is business intelligence passé? This is not exactly a question one would expect to hear posed aloud at gathering convened by Cary, N.C.-based SAS Institute Inc. Yet, at its Global Forum Executive Conference 2009, Jim Davis, SVP and chief marketing officer for SAS, pondered the notion in an address to the conference.

“Business intelligence is just too broad a term,” Davis said, noting that “business analytics” is a more an apt signifier. Moreover, Davis said, viewing business analytics purely as a technology and not as a business practice was similarly ill-advised. An enterprise-level focus on analytics will be especially important, Davis added, as the size of the digital universe expands and companies need skills and practices in place to deal with exabytes of data, much of it unstructured.

This wide view has practical implications for insurers, says Stuart Rose, marketing manager, Global Insurance for SAS. Rose notes the new fraud framework available from SAS—a social network analysis tool to help insurers visualize linkages between entities to ferret out systemic fraud.

Rose says risk scoring and anomaly detection embedded in the framework will help carriers better deploy special investigative units. “The efficiency of SIU units is greatly enhanced because the number of false positives falls to around one in 30 from one in three,” he says.

Claims data is just one of sources of information that Eric Webster, VP of marketing for Bloomington, Ill.,-basedState Farm Mutual Automobile Insurance Co. may utilize as a feedstock for analytics. Webster uses a blend of internal and external data sources to help tailor the insurer’s message to customers.

“If we can use the data to focus the message or the message timing, it’s a good thing for us,” Webster says, noting that to achieve a holistic view of the customer, he needs to extract data from all lines of business. “Like most big companies, our individual product lines tend to have ordering systems that are siloed,” he says. “Our trick is integrating them.”

This entails harvesting data from silos, putting it in a warehouse and manipulating it from there. Here, Webster can avail himself of State Farm’s robust client-server infrastructure.

But what about carriers that don’t have State Farm’s backbone or budget?

Rose notes that SAS’s new fraud framework is modular. “It’s dependent on how much an insurance company wants to implement at each stage,” he says. “What we’re emphasizing is the ability to add capabilities at later date, so you don’t have to buy this all-encompassing system on day one.”

Another option for carriers is on-demand services. SAS also announced plans to construct a 38,000-square-foot cloud computing facility that will include two massive server farms and help the company offer hosted analytics solutions.

While a cloud offering may appeal to smaller and mid-sized carriers, Webster doesn’t think it would be a good fit for State Farm. “I don’t think that’s something that would work well for us in the long term, just because of the amount of data that we have,” he says. “When you move terabytes a day, that probably not the best use of [cloud] technology.”

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